DCO Is not a Solution, It’s a Production Problem

December 1, 2020 By Celtra

Illustration: Matija Medved

Dynamic creative optimization (DCO)  is a display ad technology that has been around for almost a decade now. In an ideal world, DCO would help marketers connect with and convert consumers with ads personalized based on various data points.

In the real world, not so much. 

As a creative software company that has been around just as long as DCO has, we can proclaim that; DCO technology doesn’t work and in-house marketing teams shouldn’t buy it.

Why are we so sure of it? At Celtra, we tried it and failed at it, too. Yet, along the way, we discovered a new way to help brands personalize creative at scale. As a result we’ve gained massive traction with a different approach.

If you look at the DCO space, many of the companies founded a decade ago don’t exist anymore or struggle to go by as small-scale start-ups. It’s because DCO technology doesn’t work, but DCO as a strategy does work. 

Let us explain why.

In the past, Celtra was focused on helping brand marketers figure out DCO. We did this by building A/B testing, randomized controlled trials, machine learning, and dynamic serving. We worked with dozens of big brand clients and each time, the list of DCO problems grew. 

Marketers experienced double the ad serving costs and audience fees. They complained about disconnected reporting where creative analytics were separate from their media reports, and even saw creative quality take a hit.

It was early in 2019 that we had a realization on why there was so much friction. 

Advertisers, with their media teams, agencies, strategists, DMPs, customer journey platforms, ad servers, and buying platforms, were (and are) able to achieve the who, when, and where of personalized advertising. But they never had the what: the message and creative itself.

The problem lay in creative production for DCO. And it still does.

The production of personalized creative was too slow and cumbersome and wasn’t keeping pace. The explosion of channels, audiences, sizes, and designs increased with personalization, and the demand for content has quickly exceeded the capacity to produce it. 


DCO as a Production and Workflow Challenge


We realized that DCO is mostly a creative production and workflow challenge, not an ad serving or decisioning challenge. There’s an enormous Content Gap in between the creative assets teams have and what their media plans require. Media teams simply don’t have the assets they need. And too often, this problem is turned into an ad serving problem. The industry still believes that dynamic creative optimization can somehow fill the Content Gap between global creative toolkits and local media plans. It doesn’t.

The Content Gap manifests itself into a range of challenges within large organizations:

  • Hiring more resources to scale content becomes cost prohibitive (or not an option)
  • Being able to utilize all the household preference data is wasted with generic creative
  • Creative quality decreases as designers spend less time on each piece of content in the rush to meet deadlines
  • The process becomes slower and cumbersome, from review and approval to launch and distribution. This means marketing teams aren’t able to react to global events and cultural moments at the speed they need

Instead, teams need scalable content production, automated faster marketing but also unique brand voice and message and engaging and delightful creative.

To conclude, the technology industry is failing advertisers by positioning DCO as something you can buy and magically turn on. This is not true. The truth is DCO is a way of marketing that is the outcome of three parts: 

  • Audience strategy and logic +
  • Ad decisioning, serving and reporting +
  • Automated content production

Look at how the walled-gardens are approaching DCO and personalized ads – they ask advertisers to submit infinite content elements first, and then they run algorithms to determine which creative works best. That’s the right approach – separating out creative production from ad assembly and audience strategy. 

Rather than trying to solve the challenge through ad serving, marketers should add a SaaS layer that takes on the content production challenge. We call this technology Creative Automation. This way, marketing teams can design and generate custom assets for personalization while maintaining brand integrity and artistry.

We understand how complex it is for a business to transform from static creative to dynamic creative. We believe that separating Creative Production from Audience Strategy/Logic and Ad Decisioning/Serving/Reporting increases the likelihood of  brand success. 

Whether we are fortunate enough to get the chance to partner with you on this journey or not, we hope this insight will help you in whatever direction you take.